The present invention relates to bacteriological testing and to food processing.
Increasing publicity surrounding outbreaks of foodborne illness, and political pressure on the part of consumer groups have intensified the need for developing effective methods for detecting microorganisms in food and or eliminating them from the food chain. In the current climate of public awareness, a single outbreak of foodborne illness or even the identification of a contaminated product can be devastating. While pre-harvest and post-harvest intervention strategies are ultimately the best places to address microbial contamination, solutions at these levels will require long-term research commitments and may require implementation of substantial changes to the operation of food-growing enterprises. On the other hand, development of efficient testing methodologies may provide near-term solutions for reducing the amount of contaminated product that reaches the market. Despite the importance of this problem, state of the art testing methods remain limited in scope, are labor intensive, and are incapable of providing real-time information. The primary obstacles to fast and convenient testing are imposed by biophysical constraints on the system and sampling. In the absence of approaches to overcome these constraints in the near future, we are left with the question of how to upgrade current testing methodologies.
One clearly desirable goal for microbial monitoring systems would be the development of rapid methodologies capable of high throughput and broad application. However, constraints on the biochemical and biophysical processes that govern the sensitivity and specificity of many state of the art tests must be overcome before advances in real-time detection can be made. Currently, the technology for doing so is rudimentary at best, works only in pure solutions, and is generally not cost-effective. Testing is therefore generally completed only after-the-fact and monitoring of already packaged, sterilized food results in the recall of entire batches from the shelves.
Even though improvements in real-time detection technologies are not immediately forthcoming, applicant has realized that certain other forms of testing, together with the predictive power achievable with computational analysis of the test results, may achieve significant advances over the currently available tests and test methodologies.